The document discusses key concepts in entity-relationship (ER) modeling including: - Entities can represent real-world objects and have attributes that identify them. Common entities in a school database may be students, teachers, classes, and courses. - Relationships define associations between entities, such as a student enrolling in a course. Relationships have cardinalities that specify how many entities can be connected. - Attributes of entities can be simple, composite, derived or multi-valued. Keys uniquely identify entities and can be candidate or primary keys. - ER diagrams visually represent these concepts through entities, relationships, and attributes.

2. Introduction
 The ER model defines the conceptual view of a
database.
 It works around real-world entities and the
associations among them.
 At view level, the ER model is considered a good
option for designing databases.

3. Basic Terms
 An entity can be a real-world object, either animate or
inanimate, that can be easily identifiable.
 For example, in a school database, students, teachers,
classes, and courses offered can be considered as
entities.
 All these entities have some attributes or properties
that give them their identity

4. Basic Terms
 Entities are represented by means of their properties,
called attributes.
 All attributes have values.
 For example, a student entity may have name, class,
and age as attributes.

5. Types of Attributes
 Simple attribute − Simple attributes are atomic values, which cannot
be divided further. For example, a student's phone number is an atomic
value of 10 digits.
 Composite attribute − Composite attributes are made of more than
one simple attribute. For example, a student's complete name may have
first_name and last_name.
 Derived attribute − Derived attributes are the attributes that do not
exist in the physical database, but their values are derived from other
attributes present in the database.
 For example, average_salary in a department should not be saved
directly in the database, instead it can be derived. For another example,
age can be derived from data_of_birth.

6. Types of Attributes
 Single-value attribute − Single-value attributes
contain single value.
 For example − Social_Security_Number.
 Multi-value attribute − Multi-value attributes may
contain more than one values.
 For example, a person can have more than one phone
number, email_address, etc.

7. Basic Terms
 Entity-Set and Keys
 Key is an attribute or collection of attributes that
uniquely identifies an entity among entity set.
 For example, the roll_number of a student makes
him/her identifiable among students.
 Super Key − A set of attributes (one or more) that
collectively identifies an entity in an entity set.

8. Basic Terms
 Candidate Key − A minimal super key is called a
candidate key. An entity set may have more than one
candidate key.
 Primary Key − A primary key is one of the candidate
keys chosen by the database designer to uniquely
identify the entity set.

9. Basic Terms
 Relationship
 The association among entities is called a relationship.
 For example, an employee works_ata department, a
student enrolls in a course. Here, Works_at and
Enrolls are called relationships.

10. Basic Terms
 Relationship Set
 A set of relationships of similar type is called a
relationship set.
 Like entities, a relationship too can have attributes.
These attributes are called descriptive attributes.

11. Basic Terms
 Degree of Relationship
 The number of participating entities in a relationship
defines the degree of the relationship.
 Binary = degree 2
 Ternary = degree 3
 n-ary

12. Basic Terms
 Mapping Cardinalities
 Cardinality defines the number of entities in one
entity set, which can be associated with the number of
entities of other set via relationship set.

13. Basic Terms

14. Basic Terms

15. Basic Terms

16. Basic Terms

17. ER Representation

18. ER Representation

19. ER Representation

20. ER Representation

21. ER Representation

22. ER Representation

23. ER Representation

24. ER Representation

25. ER Representation

26. Weak and Strong Entity
 A weak entity is an entity that depends on the existence of
another entity. In more technical terms it can defined as an
entity that cannot be identified by its own attributes.
 It uses a foreign key combined with its attributed to form the
primary key.
 An entity like order item is a good example for this.
 The order item will be meaningless without an order so it
depends on the existence of order.

27. Weak and Strong Entity

28. Weak and Strong Entity
 An entity set that has a primary key is called as Strong
entity set.
 Consider an entity set Payment which has three
attributes: payment_number, payment_date and
payment_amount.
 Although each payment entity is distinct but payment
for different loans may share the same payment
number. Thus, this entity set does not have a primary
key and it is an entity set

29. Weak and Strong Entity
 A weak entity set does not have a primary key but we
need a means of distinguishing among all those
entries in the entity set that depend on one particular
strong entity set.
 The discriminator of a weak entity set is a set of
attributes that allows this distinction be made.
 For example, payment_number acts as discriminator
for payment entity set.

30. Weak and Strong Entity
 A member of a strong entity set is called dominant
entity and member of weak entity set is called as
subordinate entity.

31. Weak and Strong Entity

32. Total and Partial Participation

33. Total and Partial Participation
 Relationships between entities can be optional or
compulsory.
 In our example, we could decide that a person is considered
to be a customer only if they have bought a product.
 On the other hand, we could say that a customer is a person
whom we know about and whom we hope might buy
something—that is, we can have people listed as customers
in our database who never buy a product

34. Total and Partial Participation
 In the first case, the customer entity has total
participation in the bought relationship (all customers
have bought a product, and we can’t have
a customer who hasn’t bought a product), while in the
second case it has partial participation (a customer can
buy a product).
 These are referred to as the participation constraints of
the relationship.

35. Total and Partial Participation
 Employee head of department
 Not all employees become a head, but department will
always be headed by one employee.
 So employee participated partially in relationship.

36. Roles

37. Example of ER Diagram
 In case of college, a college contain many departments
 Each dept. can offer any number of courses
 Many instructor can work in a dept.
 An instructor can work only in one dept.
 For each dept. there is head
 An instructor can be head of only one dept.
 Each instructor can take any no. of courses
 A course can be taken by only one instructor
 A student can enroll for any no. of courses
 Each course can have any no. of students

38. Example of ER Diagram
 Step 1 : Identify the Entities
What are the entities here?
 From the statements given, the entities are
 Department
 Course
 Instructor
 Student

39. Example of ER Diagram
 Step 2 : Identify the relationships
 One department offers many courses. But one particular course can be
offered by only one department. hence the cardinality between
department and course is One to Many (1:N)
 One department has multiple instructors . But instructor belongs to
only one department. Hence the cardinality between department and
instructor is One to Many (1:N)
 One department has only one head and one head can be the head of
only one department. Hence the cardinality is one to one. (1:1)
 One course can be enrolled by many students and one student can
enroll for many courses. Hence the cardinality between course and
student is Many to Many (M:N)
 One course is taught by only one instructor. But one instructor teaches
many courses. Hence the cardinality between course and instructor is
Many to One (N :1)

40. Example of ER Diagram
 Step 3: Identify the key attributes
 "Departmen_Name" can identify a department
uniquely. Hence Department_Name is the key
attribute for the Entity "Department".
 Course_ID is the key attribute for "Course" Entity.
 Student_ID is the key attribute for "Student" Entity.
 Instructor_ID is the key attribute for "Instructor"
Entity.

41. Example of ER Diagram
 Step 4: Identify other relevant attributes
 For the department entity, other attributes are location
 For course entity, other attributes are
course_name,duration
 For instructor entity, other attributes are first_name,
last_name, phone
 For student entity, first_name, last_name, phone

42. Example of ER Diagram

43. Generalization

44. Example

45. Specialization

46. Specialization

47. Aggregation
 Aggregation is a process when relation between two
entity is treated as a single entity.
 Here the relation between Center and Course, is acting
as an Entity in relation with Visitor.

48. Aggregation

49. Aggregation
 The E-R model cannot express relationships among
relationships.
 When would we need such a thing?
 Consider a DB with information about employees who
work on a particular project and use a number of
machines doing that work.

50. Aggregation

51. Aggregation
 Relationship sets work and uses could be combined into a
single set. However, they shouldn't be, as this would
obscure the logical structure of this scheme.
 The solution is to use aggregation.
 An abstraction through which relationships are treated as
higher-level entities.
 For our example, we treat the relationship set work and the
entity sets employee and project as a higher-level entity
set called work.

52. Aggregation